Complex Adaptive Systems: An Introduction to Computational Models of Social Life

Complex Adaptive Systems: An Introduction to Computational Models of Social Life

John H. Miller
Scott E. Page
Copyright Date: 2007
Edition: STU - Student edition
Pages: 284
https://www.jstor.org/stable/j.ctt7s3kx
  • Cite this Item
  • Book Info
    Complex Adaptive Systems: An Introduction to Computational Models of Social Life
    Book Description:

    This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations,Complex Adaptive Systemsfocuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents.

    John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

    eISBN: 978-1-4008-3552-2
    Subjects: Sociology, Mathematics

Table of Contents

  1. Front Matter
    (pp. i-vi)
  2. Table of Contents
    (pp. vii-xii)
  3. List of Figures
    (pp. xiii-xiv)
  4. List of Tables
    (pp. xv-xvi)
  5. Preface
    (pp. xvii-xx)
  6. Part I Introduction
    • CHAPTER 1 Introduction
      (pp. 3-8)

      Adaptive social systems are composed of interacting, thoughtful (but perhaps not brilliant) agents. It would be difficult to date the exact moment that such systems first arose on our planet—perhaps it was when early single-celled organisms began to compete with one another for resources or, more likely, much earlier when chemical interactions in the primordial soup began to self-replicate. Once these adaptive social systems emerged, the planet underwent a dramatic change where, as Charles Darwin noted, “from so simple a beginning endless forms most beautiful and most wonderful have been, and are being, evolved.” Indeed, we find ourselves at...

    • CHAPTER 2 Complexity in Social Worlds
      (pp. 9-32)

      We are surrounded by complicated social worlds. These worlds are composed of multitudes of incommensurate elements, which often make them hard to navigate and, ultimately, difficult to understand. We would, however, like to make a distinction between complicated worlds and complex ones. In a complicated world, the various elements that make up the system maintain a degree of independence from one another. Thus, removing one such element (which reduces the level of complication) does not fundamentally alter the system’s behavior apart from that which directly resulted from the piece that was removed. Complexity arises when the dependencies among the elements...

  7. Part II Preliminaries
    • CHAPTER 3 Modeling
      (pp. 35-43)

      We begin with a discussion of the basics of scientific modeling. This topic is so fundamental to the scientific enterprise that it is often assumed to be known by, rather than explicitly taught to, students (with the exception of a high school lecture or two on the “scientific method”). For whatever reasons, learning about modeling is a lot like learning about sex: despite its importance, most people do not want to discuss it, and no matter how much you read about it, it just doesn’t seem the same when you actually get around to doing it.

      All modeling requires the...

    • CHAPTER 4 On Emergence
      (pp. 44-54)

      Much of the focus of complex systems is on how systems of interacting agents can lead to emergent phenomena. Unfortunately, emergence is one of those complex systems ideas that exists in a well-trodden, but relatively untracked, bog of discussion. The usual notion put forth underlying emergence is that individual, localized behavior aggregates into global behavior that is, in some sense, disconnected from its origins. Such a disconnection implies that, within limits, the details of the local behavior do not matter to the aggregate outcome. Clearly such notions are important when considering the decentralized systems that are key to the study...

  8. Part III Computational Modeling
    • CHAPTER 5 Computation as Theory
      (pp. 57-77)

      For many centuries, houses were constructed by their occupants with perhaps the assistance of a few skilled neighbors. This vernacular architecture led to the creation of unique homes, each reflecting the whims of its builders. Various additions and deletions would accrue over time as the needs of the family changed. Houses were designed with both local materials and conditions in mind. The soundness of such structures was dependent on both luck and the innate engineering skill of each owner—on many occasions a house would collapse due to poor design.

      With time, ideas about appropriate home design and construction became...

    • CHAPTER 6 Why Agent-Based Objects?
      (pp. 78-90)

      Agent-based object models offer a new theoretical portal from which to explore complex adaptive social systems. Like any theoretical tool, these models have comparative advantages for certain types of explorations. In fact, their advantages appear particularly well suited, and perhaps even necessary, for helping us to understand better the types of problems that arise in the study of complex adaptive social systems. Many of our existing tools tend to purify the theoretical waters so much so that we are often left with a model that is barren of any useful signs of social life. Tools like agent-based object models allow...

  9. Part IV Models of Complex Adaptive Social Systems
    • CHAPTER 7 A Basic Framework
      (pp. 93-113)

      Complex adaptive social systems are composed of interacting, thoughtful (but perhaps not brilliant) agents. Given this underlying structure, models of these systems, especially those that rely on agent-based objects, tend to confront a common set of issues. In this chapter, we discuss some of these issues in hopes of illuminating the core modeling elements and building some overall coherence. We make no presumptions that the modeling paths we suggest here are inherently superior to other possible approaches, and we suspect that there are likely to be many productive alternatives.¹

      Given our focus on interacting systems of agents, it would be...

    • CHAPTER 8 Complex Adaptive Social Systems in One Dimension
      (pp. 114-140)

      We begin with a set of very simple models designed to illuminate some basic issues inherent in complex adaptive social systems. In Abbott’sFlatland, geometric figures confined to living in a two-dimensional world gain insight into the third-dimension when a sphere slowly passes through their plane. The sphere begins as a point, grows into ever larger circles, eventually reverses its course and returns to a point, and disappears. After seeing this amazing sequence of activity, the figures confined to Flatland begin to glimpse the third dimension. Here we explore some simple models with a similar motivation to Abbott’s sphere, namely,...

    • CHAPTER 9 Social Dynamics
      (pp. 141-177)

      To further our investigation of complex adaptive social systems, here we create some models with more elaborate agent dynamics. These dynamics allow us to investigate new realms of social behavior, and the resulting models can be used to explore topics such as racial segregation, the role of expectations on behavior, and city formation. Moreover, we also consider some new concepts surrounding equilibrium analysis and self-organization in social systems.

      Our first model considers a system composed of a single agent who maneuvers in physical space. A single agent does not a society make, so to transform this into a model of...

    • CHAPTER 10 Evolving Automata
      (pp. 178-199)

      Models where agents adapt their behavior based on experience are very useful in the exploration of complex adaptive social systems. In many social systems, agents are not static behavioral drones; rather, they alter their behavior based on past feedback or the anticipation of future events. A key scientific question is how does adaptation alter the dynamics of complex systems. From a modeling perspective, the introduction of adaptive agents provides a means by which to create models that can explore new realms of agent behavior that transcend the usual bounds imposed by the modeler. From a practical point of view, if...

    • CHAPTER 11 Some Fundamentals of Organizational Decision Making
      (pp. 200-210)

      Organizations composed of collections of agents influence the behavior of systems ranging from biochemical and neurological pathways to political parties and firms. Like all decision-making entities, these organizations must formulate productive actions based on information from their environment. Here, we investigate some fundamental principles underlying this process. We develop these principles by analyzing a model of decentralized decision making that allows us to explore a well-defined class of organizational structures immersed in an ensemble of potential problems. Our goal is to understand better some of the key “natural” constraints governing all organizational systems. The questions we confront include: What are...

  10. Part V Conclusions
    • CHAPTER 12 Social Science in Between
      (pp. 213-226)

      Here we discuss the impact of complex adaptive systems on the social sciences. Our book’s central theme, “The Interest in Between,” provides a framing for this discussion. The complex adaptive social systems view of the world allows us to explore the spaces between simple and strategic behavior, between pairs and infinities of agents, between equilibrium and chaos, between richness and rigor, and between anarchy and control. These spaces lie between what we currently know and what we need to know. They are not subtle refinements on the landscape of knowledge but represent substantial deviations from what we typically assume. The...

    • Epilogue
      (pp. 227-230)

      Here we have explored models that from simple beginnings result in systems imbued with scientific beauty and mystery. The precise and simple details of each model are fully responsible for, yet simultaneously rather removed from, the majesty of the resulting outcomes. We find ourselves immersed in a world that lies between the micro and macro, that twists our experiences and expectations, and that hints at the interest in between the usual boundaries we impose on our models. We are on the edge of a vast frontier, where the exquisite composition of what once was a distant world is beginning to...

  11. Appendixes
    • APPENDIX A An Open Agenda for Complex Adaptive Social Systems
      (pp. 231-244)
    • APPENDIX B Practices for Computational Modeling
      (pp. 245-254)
  12. Bibliography
    (pp. 255-260)
  13. Index
    (pp. 261-264)